{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib\n",
    "matplotlib.rcParams['image.interpolation'] = 'nearest'\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Image processing and machine learning\n",
    "\n",
    "Some image processing numerical techniques are very specific to image processing, such as mathematical morphology or anisotropic diffusion segmentation. However, it is also possible to adapt generic machine learning techniques for image processing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A short introduction to machine learning\n",
    "\n",
    "This section is adapted from the [quick start tutorial](http://scikit-learn.org/stable/tutorial/basic/tutorial.html) from the scikit-learn documentation.\n",
    "\n",
    "In general, a learning problem considers a set of N samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features.\n",
    "\n",
    "Typical machine learning tasks are :\n",
    "- **classification**: samples belong to two or more classes and we want to learn from already labeled data how to predict the class of unlabeled data. For example, given examples of pixels belonging to an object of interest and background, we want the algorithm to label all the other pixels of the image. Or given images of cats and dogs, we want to label automatically images whether they show cats or dogs.\n",
    "- **clustering**: grouping together similar samples. For example, given a set of pictures, can we group them automatically by suject (e.g. people, monuments, animals...)?\n",
    "\n",
    "In image processing, a sample can either be\n",
    "- a whole image, its features being pixel values, or sub-regions of an image (e.g. for face detection)\n",
    "- a pixel, its features being intensity values in colorspace, or statistical information about a neighbourhood centered on the pixel,\n",
    "- a labeled region, e.g. for classifying particles in an image of labels\n",
    "\n",
    "The only requirement is to create a dataset composed of N samples, of m features each, which can be passed to the **estimators** of scikit-learn.\n",
    "\n",
    "Let us start with an example, using the **digits dataset** from scikit-learn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn import datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'data': array([[ 0.,  0.,  5., ...,  0.,  0.,  0.],\n",
      "       [ 0.,  0.,  0., ..., 10.,  0.,  0.],\n",
      "       [ 0.,  0.,  0., ..., 16.,  9.,  0.],\n",
      "       ...,\n",
      "       [ 0.,  0.,  1., ...,  6.,  0.,  0.],\n",
      "       [ 0.,  0.,  2., ..., 12.,  0.,  0.],\n",
      "       [ 0.,  0., 10., ..., 12.,  1.,  0.]]), 'target': array([0, 1, 2, ..., 8, 9, 8]), 'target_names': array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), 'images': array([[[ 0.,  0.,  5., ...,  1.,  0.,  0.],\n",
      "        [ 0.,  0., 13., ..., 15.,  5.,  0.],\n",
      "        [ 0.,  3., 15., ..., 11.,  8.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  4., 11., ..., 12.,  7.,  0.],\n",
      "        [ 0.,  2., 14., ..., 12.,  0.,  0.],\n",
      "        [ 0.,  0.,  6., ...,  0.,  0.,  0.]],\n",
      "\n",
      "       [[ 0.,  0.,  0., ...,  5.,  0.,  0.],\n",
      "        [ 0.,  0.,  0., ...,  9.,  0.,  0.],\n",
      "        [ 0.,  0.,  3., ...,  6.,  0.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  0.,  1., ...,  6.,  0.,  0.],\n",
      "        [ 0.,  0.,  1., ...,  6.,  0.,  0.],\n",
      "        [ 0.,  0.,  0., ..., 10.,  0.,  0.]],\n",
      "\n",
      "       [[ 0.,  0.,  0., ..., 12.,  0.,  0.],\n",
      "        [ 0.,  0.,  3., ..., 14.,  0.,  0.],\n",
      "        [ 0.,  0.,  8., ..., 16.,  0.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  9., 16., ...,  0.,  0.,  0.],\n",
      "        [ 0.,  3., 13., ..., 11.,  5.,  0.],\n",
      "        [ 0.,  0.,  0., ..., 16.,  9.,  0.]],\n",
      "\n",
      "       ...,\n",
      "\n",
      "       [[ 0.,  0.,  1., ...,  1.,  0.,  0.],\n",
      "        [ 0.,  0., 13., ...,  2.,  1.,  0.],\n",
      "        [ 0.,  0., 16., ..., 16.,  5.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  0., 16., ..., 15.,  0.,  0.],\n",
      "        [ 0.,  0., 15., ..., 16.,  0.,  0.],\n",
      "        [ 0.,  0.,  2., ...,  6.,  0.,  0.]],\n",
      "\n",
      "       [[ 0.,  0.,  2., ...,  0.,  0.,  0.],\n",
      "        [ 0.,  0., 14., ..., 15.,  1.,  0.],\n",
      "        [ 0.,  4., 16., ..., 16.,  7.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  0.,  0., ..., 16.,  2.,  0.],\n",
      "        [ 0.,  0.,  4., ..., 16.,  2.,  0.],\n",
      "        [ 0.,  0.,  5., ..., 12.,  0.,  0.]],\n",
      "\n",
      "       [[ 0.,  0., 10., ...,  1.,  0.,  0.],\n",
      "        [ 0.,  2., 16., ...,  1.,  0.,  0.],\n",
      "        [ 0.,  0., 15., ..., 15.,  0.,  0.],\n",
      "        ...,\n",
      "        [ 0.,  4., 16., ..., 16.,  6.,  0.],\n",
      "        [ 0.,  8., 16., ..., 16.,  8.,  0.],\n",
      "        [ 0.,  1.,  8., ..., 12.,  1.,  0.]]]), 'DESCR': \"Optical Recognition of Handwritten Digits Data Set\\n===================================================\\n\\nNotes\\n-----\\nData Set Characteristics:\\n    :Number of Instances: 5620\\n    :Number of Attributes: 64\\n    :Attribute Information: 8x8 image of integer pixels in the range 0..16.\\n    :Missing Attribute Values: None\\n    :Creator: E. Alpaydin (alpaydin '@' boun.edu.tr)\\n    :Date: July; 1998\\n\\nThis is a copy of the test set of the UCI ML hand-written digits datasets\\nhttp://archive.ics.uci.edu/ml/datasets/Optical+Recognition+of+Handwritten+Digits\\n\\nThe data set contains images of hand-written digits: 10 classes where\\neach class refers to a digit.\\n\\nPreprocessing programs made available by NIST were used to extract\\nnormalized bitmaps of handwritten digits from a preprinted form. From a\\ntotal of 43 people, 30 contributed to the training set and different 13\\nto the test set. 32x32 bitmaps are divided into nonoverlapping blocks of\\n4x4 and the number of on pixels are counted in each block. This generates\\nan input matrix of 8x8 where each element is an integer in the range\\n0..16. This reduces dimensionality and gives invariance to small\\ndistortions.\\n\\nFor info on NIST preprocessing routines, see M. D. Garris, J. L. Blue, G.\\nT. Candela, D. L. Dimmick, J. Geist, P. J. Grother, S. A. Janet, and C.\\nL. Wilson, NIST Form-Based Handprint Recognition System, NISTIR 5469,\\n1994.\\n\\nReferences\\n----------\\n  - C. Kaynak (1995) Methods of Combining Multiple Classifiers and Their\\n    Applications to Handwritten Digit Recognition, MSc Thesis, Institute of\\n    Graduate Studies in Science and Engineering, Bogazici University.\\n  - E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika.\\n  - Ken Tang and Ponnuthurai N. Suganthan and Xi Yao and A. Kai Qin.\\n    Linear dimensionalityreduction using relevance weighted LDA. School of\\n    Electrical and Electronic Engineering Nanyang Technological University.\\n    2005.\\n  - Claudio Gentile. A New Approximate Maximal Margin Classification\\n    Algorithm. NIPS. 2000.\\n\"}\n"
     ]
    }
   ],
   "source": [
    "digits = datasets.load_digits()\n",
    "print(digits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset is a dictionary-like object that holds all the data and some metadata about the data. This data is stored in the ``.data`` member, which is a ``n_samples, n_features`` array. Response variables (if available, as here) are stored in the ``.target member.``"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 64)\n",
      "(1797,)\n"
     ]
    }
   ],
   "source": [
    "print(digits.data.shape)\n",
    "print(digits.target.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the shape of the ``data`` array, we see that there are 1797 samples, each having 64 features. In fact, these 64 pixels are the raveled values of an 8x8 image. For convenience, the 2D images are also provided as in the ``.images`` member. In a machine learning problem, a sample always consists of a **flat array** of features, which sometimes require reshaping data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 8, 8)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(digits.images.shape)\n",
    "np.all(digits.data[0].reshape((8, 8)) == digits.images[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "target:  0\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(digits.images[0], cmap='gray')\n",
    "print(\"target: \", digits.target[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now use one of scikit-learn's estimators classes in order to predict the digit from an image. \n",
    "\n",
    "Here we use an SVC (support vector machine classification) classifier, which uses a part of the dataset (the **training set**) to find the best way to separate the different classes. Even without knowing the details of the SVC, we can use it as a black box thanks to the common estimator API of scikit-learn. An estimator is created by initializing an estimator object: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn import svm\n",
    "clf = svm.SVC(gamma=0.001, C=100.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The estimator is trained from the learning set using its ``.fit`` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=100.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape='ovr', degree=3, gamma=0.001, kernel='rbf',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(digits.data[:-10], digits.target[:-10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then the target value of new data is predicted using the ``.predict`` method of the estimator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9 8]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fc6503e5c88>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(clf.predict(digits.data[-2:]))\n",
    "fig, axes = plt.subplots(1, 2)\n",
    "axes[0].imshow(digits.images[-2], cmap='gray')\n",
    "axes[1].imshow(digits.images[-1], cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far, so good? We completed our first machine learning example!\n",
    "\n",
    "In the following, we will see how to use machine learning for image processing. We will use different kinds of samples and features, starting from low-level pixel-based features (e.g. RGB color), to mid-level features (e.g. corner, patches of high contrast), and finally to properties of segmented regions. \n",
    "\n",
    "**Outline**\n",
    "\n",
    "- Image segmentation using pixel-based features (color and texture)\n",
    "- Panorama stitching / image registration based on mid-level features\n",
    "- Classifying labeled objects using their properties\n",
    "\n",
    "**What we will not cover** \n",
    "\n",
    "- computer vision: automatic detection / recognition of objects (faces, ...)\n",
    "\n",
    "**A follow-up by Stéfan after this part** : image classification using deep learning with Keras."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thresholding and vector quantization\n",
    "\n",
    "Image binarization is a common operation. For grayscale images, finding the best threshold for binarization can be a manual operation. Alternatively, algorithms can select a threshold value automatically; which is convenient for computer vision, or for batch-processing a series of images.\n",
    "\n",
    "Otsu algorithm is the most famous thresholding algorithm. It maximizes the variance between the two segmented groups of pixels. Therefore, it is can be interpreted as a **clustering** algorithm. Samples are pixels and have a single feature, which is their grayscale value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage import data, exposure, filters\n",
    "camera = data.camera()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "hi = exposure.histogram(camera)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "val = filters.threshold_otsu(camera)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7fc644955470>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2)\n",
    "axes[0].imshow(camera, cmap='gray')\n",
    "axes[0].contour(camera, [val], colors='y')\n",
    "axes[1].plot(hi[1], hi[0])\n",
    "axes[1].axvline(val, ls='--')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How can we transpose the idea of Otsu thresholding to RGB or multichannel images? We can use the k-means algorithm, which aims to partition samples in k clusters, where each sample belongs to the cluster of nearest mean. \n",
    "\n",
    "Below we show a simple example of k-means clustering, based on the Iris dataset of ``scikit-learn``. Note that the ``KMeans`` estimator\n",
    "uses a similar API as the SVC we used for digits classification, with the .fit method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Petal length')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# From http://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_iris.html\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "np.random.seed(5)\n",
    "\n",
    "iris = datasets.load_iris()\n",
    "X = iris.data\n",
    "y = iris.target\n",
    "\n",
    "clf = KMeans(n_clusters=3)\n",
    "              \n",
    "fig = plt.figure(figsize=(4, 3))\n",
    "ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
    "clf.fit(X)\n",
    "labels = clf.labels_\n",
    "\n",
    "ax.scatter(X[:, 3], X[:, 0], X[:, 2], c=labels.astype(np.float), cmap='jet')\n",
    "\n",
    "ax.w_xaxis.set_ticklabels([])\n",
    "ax.w_yaxis.set_ticklabels([])\n",
    "ax.w_zaxis.set_ticklabels([])\n",
    "ax.set_xlabel('Petal width')\n",
    "ax.set_ylabel('Sepal length')\n",
    "ax.set_zlabel('Petal length')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "k-means clustering uses the Euclidean distance in feature space to cluster samples. If we want to cluster together pixels of similar color, the RGB space is not well suited since it mixes together information about color and light intensity. Therefore, we first transform the RGB image into [Lab colorspace](https://en.wikipedia.org/wiki/Lab_color_space), and only use the color channels (a and b) for clustering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from skimage import io, color\n",
    "im = io.imread('../images/round_pill.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "im_lab = color.rgb2lab(im)\n",
    "data = np.array([im_lab[..., 1].ravel(), im_lab[..., 2].ravel()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we create a ``KMeans`` estimator for two clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "kmeans = KMeans(n_clusters=2, random_state=0).fit(data.T)\n",
    "segmentation = kmeans.labels_.reshape(im.shape[:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fc63cc7c5c0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(im)\n",
    "plt.contour(segmentation, colors='y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course we can generalize this method to more than two clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "im = io.imread('../images/chapel_floor.png')\n",
    "im_lab = color.rgb2lab(im)\n",
    "data = np.array([im_lab[..., 0].ravel(),\n",
    "                 im_lab[..., 1].ravel(),\n",
    "                 im_lab[..., 2].ravel()])\n",
    "\n",
    "kmeans = KMeans(n_clusters=4, random_state=0).fit(data.T)\n",
    "segmentation = kmeans.labels_.reshape(im.shape[:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 375.5, 276.5, -0.5)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_mean = color.label2rgb(segmentation, im, kind='mean')\n",
    "fig, axes = plt.subplots(1, 2)\n",
    "axes[0].imshow(im)\n",
    "axes[0].axis('off')\n",
    "axes[1].imshow(color_mean)\n",
    "axes[1].axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise:\n",
    "\n",
    "For the chapel floor image, cluster the image in 3 clusters, using only the color channels (not the lightness one). What happens?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SLIC algorithm: clustering using color and spatial features\n",
    "\n",
    "In the thresholding / vector quantization approach presented above, pixels are characterized only by their color features. However, in most images neighboring pixels correspond to the same object. Hence, information on spatial proximity between pixels can be used in addition to color information.\n",
    "\n",
    "SLIC (Simple Linear Iterative Clustering) is a segmentation algorithm which clusters pixels in both space and color. Therefore, regions of space that are similar in color will end up in the same segment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fc63cb69438>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "spices = io.imread('../images/spices.jpg')\n",
    "plt.imshow(spices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us try to segment the different spices using the previous k-means approach. One problem is that there is a lot of texture coming from the relief and shades."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "im_lab = color.rgb2lab(spices)\n",
    "data = np.array([im_lab[..., 1].ravel(),\n",
    "                 im_lab[..., 2].ravel()])\n",
    "\n",
    "kmeans = KMeans(n_clusters=10, random_state=0).fit(data.T)\n",
    "labels = kmeans.labels_.reshape(spices.shape[:-1])\n",
    "color_mean = color.label2rgb(labels, spices, kind='mean')\n",
    "plt.imshow(color_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage import segmentation\n",
    "plt.imshow(segmentation.mark_boundaries(spices, labels))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SLIC is a superpixel algorithm, which segments an image into patches (superpixels) of neighboring pixels with a similar color. SLIC also works in the Lab colorspace. The ``compactness`` parameter controls the relative importance of the distance in image- and color-space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage import segmentation\n",
    "segments = segmentation.slic(spices, n_segments=200, compactness=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.imshow(segmentation.mark_boundaries(spices, segments))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "result = color.label2rgb(segments, spices, kind='mean')\n",
    "plt.imshow(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the super-pixel segmentation (which is also called oversegmentation, because we end up with more segments that we want to), we can add a second clustering step to join superpixels belonging to the same spice heap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "im_lab = color.rgb2lab(result)\n",
    "data = np.array([im_lab[..., 1].ravel(),\n",
    "                 im_lab[..., 2].ravel()])\n",
    "\n",
    "kmeans = KMeans(n_clusters=5, random_state=0).fit(data.T)\n",
    "labels = kmeans.labels_.reshape(spices.shape[:-1])\n",
    "color_mean = color.label2rgb(labels, spices, kind='mean')\n",
    "plt.imshow(segmentation.mark_boundaries(spices, labels))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that other superpixel algorithms are available, such as **Felzenswalb** segmentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "result = segmentation.felzenszwalb(spices, scale=100)\n",
    "plt.imshow(color.label2rgb(result, spices, kind='mean'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.imshow(segmentation.mark_boundaries(spices, result))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise\n",
    "\n",
    "Repeat the same operations (SLIC superpixel segmentation, followed by K-Means clustering on the average color of superpixels) on the astronaut image. Vary the following parameters\n",
    "- slic: n_segments and compactness\n",
    "- KMeans: n_clusters (start with 8 for example)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from skimage import data\n",
    "astro = data.astronaut()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# solution goes here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Increasing the number of low-level features: trained segmentation using Gabor filters and random forests\n",
    "\n",
    "In the examples above, a small number of features per pixel was used: either a color triplet only, or a color triplet and its (x, y) position. However, it is possible to use other features, such as the local texture. Texture features can be obtained using Gabor filters, which are Gaussian kernels modulated by a sinusoidal wave. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# From http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_gabor.html\n",
    "from skimage import data, img_as_float\n",
    "from skimage.filters import gabor_kernel\n",
    "import scipy.ndimage as ndi\n",
    "\n",
    "shrink = (slice(0, None, 3), slice(0, None, 3))\n",
    "brick = img_as_float(data.load('brick.png'))[shrink]\n",
    "grass = img_as_float(data.load('grass.png'))[shrink]\n",
    "wall = img_as_float(data.load('rough-wall.png'))[shrink]\n",
    "image_names = ('brick', 'grass', 'wall')\n",
    "images = (brick, grass, wall)\n",
    "\n",
    "\n",
    "def power(image, kernel):\n",
    "    # Normalize images for better comparison.\n",
    "    image = (image - image.mean()) / image.std()\n",
    "    return np.sqrt(ndi.convolve(image, np.real(kernel), mode='wrap')**2 +\n",
    "                   ndi.convolve(image, np.imag(kernel), mode='wrap')**2)\n",
    "\n",
    "# Plot a selection of the filter bank kernels and their responses.\n",
    "results = []\n",
    "kernel_params = []\n",
    "for frequency in (0.1, 0.4):\n",
    "    kernel = gabor_kernel(frequency, theta=0)\n",
    "    params = 'frequency=%.2f' % (frequency)\n",
    "    kernel_params.append(params)\n",
    "    # Save kernel and the power image for each image\n",
    "    results.append((kernel, [power(img, kernel) for img in images]))\n",
    "\n",
    "fig, axes = plt.subplots(nrows=3, ncols=4, figsize=(5, 4))\n",
    "plt.gray()\n",
    "\n",
    "fig.suptitle('Image responses for Gabor filter kernels', fontsize=12)\n",
    "\n",
    "axes[0][0].axis('off')\n",
    "\n",
    "# Plot original images\n",
    "for label, img, ax in zip(image_names, images, axes[0][1:]):\n",
    "    ax.imshow(img)\n",
    "    ax.set_title(label, fontsize=9)\n",
    "    ax.axis('off')\n",
    "\n",
    "for label, (kernel, powers), ax_row in zip(kernel_params, results, axes[1:]):\n",
    "    # Plot Gabor kernel\n",
    "    ax = ax_row[0]\n",
    "    ax.imshow(np.real(kernel), interpolation='nearest')\n",
    "    ax.set_ylabel(label, fontsize=7)\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "\n",
    "    # Plot Gabor responses with the contrast normalized for each filter\n",
    "    vmin = np.min(powers)\n",
    "    vmax = np.max(powers)\n",
    "    for patch, ax in zip(powers, ax_row[1:]):\n",
    "        ax.imshow(patch, vmin=vmin, vmax=vmax)\n",
    "        ax.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define a segmentation algorithms which:\n",
    "- computes different features for Gabor filters of different scale and angle, for every pixel\n",
    "- trains a **RandomForest** classifier from user-labeled data, which are given as a mask of labels\n",
    "- and predicts the label of the remaining non-labeled pixels\n",
    "\n",
    "The RandomForest algorithm chooses automatically thresholds along the different feature directions, and also decides which features are the most significant to discriminate between the different classes. This is very useful when we don't know if all features are relevant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from skimage import filters\n",
    "from skimage import img_as_float\n",
    "\n",
    "def _compute_features(im):\n",
    "    gabor_frequencies = np.logspace(-3, 1, num=5, base=2)\n",
    "    thetas = [0, np.pi/2]\n",
    "    nb_fq = len(gabor_frequencies) * len(thetas)\n",
    "    im = np.atleast_3d(im)\n",
    "    im_gabor = np.empty((im.shape[-1], nb_fq) + im.shape[:2])\n",
    "    for ch in range(im.shape[-1]):\n",
    "        img = img_as_float(im[..., ch])\n",
    "        for i_fq, fq in enumerate(gabor_frequencies):\n",
    "            for i_th, theta in enumerate(thetas):\n",
    "                tmp = filters.gabor(img, fq, theta=theta)\n",
    "                im_gabor[ch, len(thetas) * i_fq + i_th] = \\\n",
    "                                    np.abs(tmp[0] + 1j * tmp[1])\n",
    "    return im_gabor\n",
    "\n",
    "\n",
    "def trainable_segmentation(im, mask):\n",
    "    \"\"\"\n",
    "    Parameters\n",
    "    ----------\n",
    "    \n",
    "    im : ndarray\n",
    "        2-D image (grayscale or RGB) to be segmented\n",
    "        \n",
    "    mask : ndarray of ints\n",
    "        Array of labels. Non-zero labels are known regions that are used\n",
    "        to train the classification algorithm.\n",
    "    \"\"\"\n",
    "    # Define features\n",
    "    im_gabor = _compute_features(im)     \n",
    "    nb_ch, nb_fq, sh_1, sh2 = im_gabor.shape\n",
    "    # Training data correspond to pixels labeled in mask\n",
    "    training_data = im_gabor[:, :, mask>0]\n",
    "    training_data = training_data.reshape((nb_ch * nb_fq,\n",
    "                                         (mask>0).sum())).T\n",
    "    training_labels = mask[mask>0].ravel()\n",
    "    # Data are from the remaining pixels\n",
    "    data = im_gabor[:, :, mask == 0].reshape((nb_ch * nb_fq,\n",
    "                                              (mask == 0).sum())).T\n",
    "    # classification\n",
    "    clf = RandomForestClassifier()\n",
    "    clf.fit(training_data, training_labels)\n",
    "    labels = clf.predict(data)\n",
    "    result = np.copy(mask)\n",
    "    result[mask == 0] = labels\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Image from https://fr.wikipedia.org/wiki/Fichier:Bells-Beach-View.jpg\n",
    "beach = io.imread('../images/Bells-Beach.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Define mask of user-labeled pixels, which will be used for training\n",
    "mask = np.zeros(beach.shape[:-1], dtype=np.uint8)\n",
    "mask[700:] = 1\n",
    "mask[:550, :650] = 2\n",
    "mask[400:450, 1000:1100] = 3\n",
    "plt.imshow(beach)\n",
    "plt.contour(mask, colors='y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "result = trainable_segmentation(beach, mask)\n",
    "plt.imshow(color.label2rgb(result, beach, kind='mean'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using mid-level features \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage import data\n",
    "camera = data.camera()\n",
    "from skimage import feature\n",
    "corner_camera = feature.corner_harris(camera)\n",
    "coords = feature.corner_peaks(corner_camera)\n",
    "plt.imshow(camera, cmap='gray')\n",
    "plt.plot(coords[:, 1], coords[:, 0], 'o')\n",
    "plt.xlim(0, 512)\n",
    "plt.ylim(512, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Panorama stitching](example_pano.ipynb)\n",
    "\n",
    "[A longer example](adv3_panorama-stitching.ipynb)\n",
    "\n",
    "### Exercise\n",
    "\n",
    "Represent the ORB keypoint of the camera-man"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# solution goes here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Clustering or classifying labeled objects\n",
    "\n",
    "We have already seen how to use ``skimage.measure.regionprops`` to extract the properties (area, perimeter, ...) of labeled objects. These properties can be used as features in order to cluster the objects in different groups, or to classify them if given a training set.\n",
    "\n",
    "In the example below, we use ``skimage.data.binary_blobs`` to generate a binary image. We use several properties to generate features: the area, the ratio between squared perimeter and area, and the solidity (which is the area fraction of the object as compared to its convex hull). We would like to separate the big convoluted particles from the smaller round ones. Here I did not want to bother with a training set, so we will juste use clustering instead of classifying."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from skimage import measure\n",
    "from skimage import data\n",
    "im = data.binary_blobs(length=1024, blob_size_fraction=0.05,\n",
    "                         volume_fraction=0.2)\n",
    "labels = measure.label(im)\n",
    "props = measure.regionprops(labels)\n",
    "\n",
    "data = np.array([(prop.area,\n",
    "                  prop.perimeter**2/prop.area,\n",
    "                  prop.solidity) for prop in props])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "plt.imshow(labels, cmap='spectral')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once again we use the KMeans algorithm to cluster the objects. We visualize the result as an array of labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "clf = KMeans(n_clusters=2)\n",
    "\n",
    "clf.fit(data)\n",
    "\n",
    "\n",
    "def reshape_cluster_labels(cluster_labels, image_labels):\n",
    "    \"\"\"\n",
    "    Some NumPy magic\n",
    "    \"\"\"\n",
    "    cluster_labels = np.concatenate(([0], cluster_labels + 1))\n",
    "    return cluster_labels[image_labels]\n",
    "    \n",
    "\n",
    "object_clusters = reshape_cluster_labels(clf.labels_, labels)\n",
    "plt.imshow(object_clusters, cmap='spectral')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, our features were not carefully designed. Since the ``area`` property can take much larger values than the other properties, it dominates the other ones. To correct this effect, we can normalize the area to its maximal value. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data[:, 0] /= data[:, 0].max()\n",
    "\n",
    "clf.fit(data)\n",
    "\n",
    "object_clusters = reshape_cluster_labels(clf.labels_, labels)\n",
    "plt.imshow(object_clusters, cmap='spectral')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A better way to do the rescaling is to use of the scaling methods provided by ``sklearn.preprocessing``. The ``StandardScaler`` makes sure that every feature has a zero mean and a unit standard deviation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "min_max_scaler = preprocessing.StandardScaler()\n",
    "data_scaled = min_max_scaler.fit_transform(data)\n",
    "\n",
    "clf = KMeans(n_clusters=2)\n",
    "\n",
    "clf.fit(data_scaled)\n",
    "\n",
    "object_clusters = reshape_cluster_labels(clf.labels_, labels)\n",
    "plt.imshow(object_clusters, cmap='spectral')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Exercise\n",
    "\n",
    "Replace the area property by the eccentricity, so that clustering separates compact and convoluted particles, regardless of their size. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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